Artificial intelligence for forecasting and diagnosing COVID-19 pandemic: A focused review

Abstract

The outbreak of novel corona virus 2019 (COVID-19) has been treated as a public health crisis of global concern by the World Health Organization (WHO). COVID-19 pandemic hugely affected countries worldwide raising the need to exploit novel, alternative and emerging technologies to respond to the emergency created by the weak health-care systems. In this context, Artificial Intelligence (AI) techniques can give a valid support to public health authorities, complementing traditional approaches with advanced tools. This study provides a comprehensive review of methods, algorithms, applications, and emerging AI technologies that can be utilized for forecasting and diagnosing COVID-19. The main objectives of this review are summarized as follows. (i) Understanding the importance of AI approaches such as machine learning and deep learning for COVID-19 pandemic; (ii) discussing the efficiency and impact of these methods for COVID-19 forecasting and diagnosing; (iii) providing an extensive background description of AI techniques to help non-expert to better catch the underlying concepts; (iv) for each work surveyed, give a detailed analysis of the rationale behind the approach, highlighting the method used, the type and size of data analyzed, the validation method, the target application and the results achieved; (v) focusing on some future challenges in COVID-19 forecasting and diagnosing.

Keywords: Artificial intelligence; COVID-19; Deep learning; Diagnosing; Forecasting; Machine learning.

Fig. 1

ML techniques used for COVID-19 forecasting.

Fig. 2

DL techniques used for COVID-19 forecasting.

Fig. 3

Editor distribution of the publications.

Fig. 4

Data Types used for COVID-19 cases forecasting.

Fig. 5

COVID-19 Forecasting- Topics.

Fig. 6

Most performing ML and DL methods used for COVID-19 cases forecasting.